1. Field of the Invention
The present invention is directed to an arrangement for analyzing local bioelectric currents in biological tissue complexes, and in particular to such an arrangement having sensors for measuring electrical or magnetic field quantities generated by the biological electric currents.
2. Description of the Prior Art
An apparatus as described in U.S. Pat. No. 4,736,751 which analyzes brain activities on a statistical basis using a digital computer. Sensors for measuring the electrical and/or magnetic field characteristics of brain currents are distributed in a standard manner over a cranial cap. The measured signals are converted into digital form and stored. The patient being examined is subjected to a set of sensory stimuli which trigger electrical or magnetic fields in localized regions of the brain. The sensors convert these fields into electrical signals which are statistically evaluated and analyzed in order to verify the location of the activity. On the basis of the spatial and temporal-relationships of these spontaneous events, the location of their source and the manner of their propagation can be portrayed on a three-dimensional skull model generated, for example, by computer tomography using nuclear magnetic resonance imaging techniques.
A disadvantage of this known method is that it produces usable results only when the evoked potentials are high enough in magnitude to contrast in a clearly recognizable fashion with the noise level. This generally requires a relatively large number of stimuli to provide a large enough base for the averaging techniques. This renders this known method unsuitable for identifying spontaneous events such as occur, for example, in an epileptic seizure. It is known that the spontaneous events associated with an epileptic seizure can be identified in the electroencephalogram (EEG) as characteristic patterns, referred to as "spike and wave complexes," having a duration of about 200 through 500 ms. These signal patterns are also identifiable between acute seizures, however, with a very different frequency from patient to patient. In extreme cases, such signal patterns can appear every second, or only once a week. As a result of the low signal-to-noise ratio, such interictal signal patterns in the EEG are usually very difficult to recognize, and then only by experienced neurologists. Such signals are virtually unrecognizable with the naked eye in the magnetoencephalogram (MEG). The point of origin of such spontaneously appearing single patterns is interpreted as an epileptogenous seat. The goal of the interpretation of an EEG or MEG in epilepsy diagnostics is to localize the location of this seat as exactly as possible. It is also of significance for the neurologist to obtain information regarding the spatial propagation of signal-forming, electrical excitations, both within a signal pattern and in successive, different signal patterns. Such information has heretofore only been able to be obtained using invasive techniques, such as EEG depth electrodes. Even these invasive techniques yield only a limited amount of information. Moreover, a time-resolving localization is difficult or impossible to achieve because, due to the low signal-to-noise ratio, a localization having the required precision cannot be obtained based on a single signal event, and usually a sufficient number of such events is not available for a reliable averaging.
In the article "New Method for the Study of Spontaneous Brain Activity," Ilmoniemi et al., Biomagnetism 1987, Proceedings of the 6th International Conference on Biomagnetism, correlation of the local patterns of brain signals is disclosed for the purpose of recognizing spike-wave complexes. Such correlation is undertaken, however, only in an EEG channel for the detection of epileptic and alpha activities. This method is adequate only when a significant event is unambiguously recognized in a channel. It is known, however, that significant correlations of spike-wave complexes, in the context of the signal-to-noise ratio which occurs in practice, cannot be observed at all using the simple correlation function, and can only be poorly observed in the spatially and chronologically averaged correlation functions of an MEG.